Optimizing Neural Networks for Chemical Reaction Prediction: Insights from Methylene Blue Reduction Reactions
Ivan Malashin,
Vadim Tynchenko,
Andrei Gantimurov
et al.
Abstract:This paper offers a thorough investigation of hyperparameter tuning for neural network architectures using datasets encompassing various combinations of Methylene Blue (MB) Reduction by Ascorbic Acid (AA) reactions with different solvents and concentrations. The aim is to predict coefficients of decay plots for MB absorbance, shedding light on the complex dynamics of chemical reactions. Our findings reveal that the optimal model, determined through our investigation, consists of five hidden layers, each with s… Show more
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